Journal: Slas Discovery

Article Title: Secretome-Based Screening in Target Discovery

doi: 10.1177/2472555220917113

Figure Lengend Snippet: Concept of secretome-based screening—the combination of a secretome library and a cell-based assay with a disease-relevant readout results in the identification of novel targets and elucidation of signal transduction pathways. ( A ) Different responses can be measured in a secretome-based assay. (1) A secreted ligand (triangle) induces an agonist response that results in an increase in the signal of the phenotypic readout. (2) A secreted ligand functions as an antagonist and reduces the signal of the phenotypic readout. (3) A secreted ligand or ECD function as a decoy factor. (4) A secreted ligand is an enzyme, which produces a metabolite that affects the phenotypic readout. The arrows illustrate that both agonist (gray) and antagonist (black) readouts can be measured. ( B ) Novel biology and putative targets can be discovered at different stages of the secretome-based workflow.

Article Snippet: At AstraZeneca we used additional databases such as GeneOntology: “Extracellular space” annotation, Ingenuity Pathway Analysis (IPA) analysis, and an in silico survey of relevant literature, including the “Human Secretome Atlas” and specific stratification for cardiac cells, – for the library described above.

Techniques: Cell Based Assay, Transduction

Journal: Slas Discovery

Article Title: Secretome-Based Screening in Target Discovery

doi: 10.1177/2472555220917113

Figure Lengend Snippet: The secretome library—the constituents, how to produce it, information flow, and sample management. ( A ) Annotation of the KTH secretome library comprising more than 1500 produced secreted proteins and ECDs. Secreted proteins can be divided into different subcategories based on Uniprot keywords for molecular function and/or biological process. The circle diagram shows the division into subfamilies as indicated. ( B ) Overview of protein production. (1) Bioinformatics to design constructs for all human secreted proteins and selected ECDs of one-pass TM proteins. (2) Gene synthesis and custom cloning of the constructs followed by sequence verification. (3) Plasmid preparation and additional sequence verification before entering the protein production. (4) Protein expression using the episomal QMCF vector in CHO cells. (5) Protein purification using the C-terminal HPC4 tag. (6) Protein quality check. ( C ) Overview of the information flow and sample management process. (1) Purified proteins in 2D barcoded vials. (2) Protein batches were thawed once and dispensed into subaliquots (15–20 µL) that were snap-frozen in liquid nitrogen. (3) Aliquots were stored at −80 °C until tested in the cell-based screens. (4) Proteins were dispensed and diluted in 384-well plates before addition to cell-based assays. (5) Data information handling. The library is registered in AstraZeneca compound management databases to allow for the integration between compound handling, assay screening, and data analysis.

Article Snippet: At AstraZeneca we used additional databases such as GeneOntology: “Extracellular space” annotation, Ingenuity Pathway Analysis (IPA) analysis, and an in silico survey of relevant literature, including the “Human Secretome Atlas” and specific stratification for cardiac cells, – for the library described above.

Techniques: Produced, Construct, Cloning, Sequencing, Plasmid Preparation, Expressing, Protein Purification, Purification

Journal: Slas Discovery

Article Title: Secretome-Based Screening in Target Discovery

doi: 10.1177/2472555220917113

Figure Lengend Snippet: The secretome-based workflow from initial screen to confirmed active. ( A ) Schematic flow diagram showing the different steps in a typical secretome-based screen using purified proteins. (1) Usually the full library is tested at three concentrations in duplicate. A small volume of secretome protein (typically 1 µL) is added to each well (typically 40–50 µL). This results in a top concentration of 200 nM protein for a majority of samples tested. Occasionally, another dose of protein is added to the cells during incubation if the assay is running for a long period of time (>3 days). (2) Actives from the primary screen are confirmed in dose response in the primary assay. (3) A list of confirmed active proteins will be annotated in silico. This involves, for example, literature searches, expression data, disease relevance, and human target validation. (4) Additional protein will be produced so that the secretome library is not depleted. (5) Annotated actives will be tested in additional biologic effect assays (BEAs) before initiating any mechanistic studies (6). ( B ) An illustrative example of one assay where two markers are measured simultaneously. , As a result, four types of actives are identified that affect the markers differently (see main text).

Article Snippet: At AstraZeneca we used additional databases such as GeneOntology: “Extracellular space” annotation, Ingenuity Pathway Analysis (IPA) analysis, and an in silico survey of relevant literature, including the “Human Secretome Atlas” and specific stratification for cardiac cells, – for the library described above.

Techniques: Purification, Concentration Assay, Incubation, In Silico, Expressing, Biomarker Discovery, Produced

Journal: Slas Discovery

Article Title: Secretome-Based Screening in Target Discovery

doi: 10.1177/2472555220917113

Figure Lengend Snippet: A summary of different steps needed to identify a receptor and signaling pathway induced by a secreted ligand. When an active has been identified from a secretome-based screen, the next step is to identify the cognate receptor and/or enzymatic activity that is needed to transduce the signal into the cells. There are several methods available to establish the identity of the receptor as described in the main text. Also, gene expression analysis can be utilized to profile the transcriptional events that are induced by the active secretome proteins. Finally, this can be confirmed by siRNA or precise genome editing (PGE). See text for more details.

Article Snippet: At AstraZeneca we used additional databases such as GeneOntology: “Extracellular space” annotation, Ingenuity Pathway Analysis (IPA) analysis, and an in silico survey of relevant literature, including the “Human Secretome Atlas” and specific stratification for cardiac cells, – for the library described above.

Techniques: Activity Assay, Transduction, Gene Expression

Journal: Slas Discovery

Article Title: Secretome-Based Screening in Target Discovery

doi: 10.1177/2472555220917113

Figure Lengend Snippet: Examples of targets discovered by secretome-based screening. , , ( A ) A secretome-based screen to identify targets that affect the viability of monocytes. IL-34 was discovered in the primary screen using primary human monocytes. The methodology used was CellTiter-Glo. The activity of IL-34 was confirmed in human bone marrow cultures (BMCs), in which IL-34 promoted the formation of macrophage progenitor cells. The receptor of IL-34 was discovered by preincubating the protein with ECDs in the secretome library and measuring cell viability. Preincubation with macrophage CSF-1R-ECD resulted in an inhibition of the effect compared with other IL-34-ECD samples. ( B ) Identification of the NKp44-PDGF-DD receptor pair. A NKp44-GFP reporter cell line was used to identify the ligand of NKp44 as PDGF-D. The activity of purified PDGF-DD was confirmed using human NK cells from donors, by measuring phosphorylation of downstream substrates Akt and Erk and by measuring proinflammatory cytokine release (interferon-γ and tumor necrosis factor). ( C ) Identification of FGF16 as a specific inducer of human CPC proliferation. The ability of secretome proteins to induce iPSC-CPC proliferation was measured by nuclear count. All actives were counterscreened in a CF proliferation assay. The interaction of FGF9 and FGF16 with CPCs and CFs was quantified using biosensor analysis. Conditioned medium libraries were used in A and B , whereas a purified protein library was used in C .

Article Snippet: At AstraZeneca we used additional databases such as GeneOntology: “Extracellular space” annotation, Ingenuity Pathway Analysis (IPA) analysis, and an in silico survey of relevant literature, including the “Human Secretome Atlas” and specific stratification for cardiac cells, – for the library described above.

Techniques: Activity Assay, Inhibition, Purification, Phospho-proteomics, Proliferation Assay

Journal: Medicine

Article Title: Bibliometric and visual analyses of research on the links between stroke and exosomes from 2008 to 2023

doi: 10.1097/MD.0000000000039498

Figure Lengend Snippet: Top 10 most-cited research papers (review).

Article Snippet: Molecular mechanisms responsible for therapeutic potential of mesenchymal stem cell-derived secretome , Randall Harrell , 254 , Cells , Regenerative Processing Plant LLC of Palm Harbor , 2019 , USA , 6.

Techniques:

Journal: International Journal of Molecular Sciences

Article Title: Manufacturing of Human Extracellular Vesicle-Based Therapeutics for Clinical Use

doi: 10.3390/ijms18061190

Figure Lengend Snippet: List of companies offering exosome-/extracellular vesicle- or secretome-based services and products.

Article Snippet: Aposcience AG , Stroke, spinal cord injury, skin lesions, acute andchronic myocardial infarction , Peripheral blood mononuclear cell secretome “APOSEC TM ” , http://www.aposcience.at/the-secretome-company/.

Techniques: Diagnostic Assay, Vaccines

Journal: Scientific Data

Article Title: An image-based screen for secreted proteins involved in breast cancer G0 cell cycle arrest

doi: 10.1038/s41597-024-03697-z

Figure Lengend Snippet: Experimental workflow. ( a ) The screen methodology is depicted starting with the primary screen, including staining, imaging, analysis and hit ranking, followed by a secondary screen of hits and bioinformatic shortlisting. Representative images of each stain are depicted, with CKI (CDK inhibitors) representing p21 or p27. The image analysis pipeline is represented by screenshots from Harmony (PerkinElmer) software. ( b ) Flow chart depicting how the secretome library was refined at each stage to a final list of proteins which induce G0 arrest.

Article Snippet: A library of 1282 secretome proteins was provided by AstraZeneca in collaboration with the Royal Institute of Technology (KTH) in Stockholm.

Techniques: Staining, Imaging, Software

Journal: Scientific Data

Article Title: An image-based screen for secreted proteins involved in breast cancer G0 cell cycle arrest

doi: 10.1038/s41597-024-03697-z

Figure Lengend Snippet: Bioinformatic analyses of hits. ( a ) Correlations between the G0 arrest score per tumour and the expression of selected secretome genes (encoding proteins that were hits in the screen) within the same tumour, calculated pan-cancer (first column) or by cancer type. Abbreviations correspond to different cancer types as defined by TCGA. Positive values (blue) indicate a positive correlation between G0 arrest levels and the expression of the respective gene, negative values (red) indicate an inverse relationship. Significant correlations (Pearson p < 0.05) are marked with an asterisk. ( b ) Correlations between the G0 arrest score and the expression of selected secretome genes across ER positive and ER negative breast cancers. Colour gradient and asterisk annotations as in (a). ( c ) Secretome genes with prognostic value in TCGA. The results from Cox proportional hazards analyses for overall survival across all cancers are shown, after adjustment for cancer type and stage. Samples with gene expression in the upper quartile were compared with those whose expression is in the lower quartile for the same gene. Positive values indicate that cases with high expression of the respective gene present worse survival.

Article Snippet: A library of 1282 secretome proteins was provided by AstraZeneca in collaboration with the Royal Institute of Technology (KTH) in Stockholm.

Techniques: Expressing

Journal: Scientific Data

Article Title: An image-based screen for secreted proteins involved in breast cancer G0 cell cycle arrest

doi: 10.1038/s41597-024-03697-z

Figure Lengend Snippet: Technical repeats for the secretome screen. Graphs to show the reproducibility of the raw data between the two replica plates for nuclear number ( a ) and EdU negative (EdU-) fraction ( b ) in MCF7 cells (p < 0.0001). Graphs to show the reproducibility of the raw data between the two replica plates for nuclear number ( c ) and EdU negative (EdU-) fraction ( d ) in hTERT-HMEC cells (p < 0.0001). Note that the data for hTERT-HMEC EdU- fraction is noisy for hTERT-HMEC cells but proteins are only called as a hit if they increased the EdU- (G0) fraction in both technical replicates.

Article Snippet: A library of 1282 secretome proteins was provided by AstraZeneca in collaboration with the Royal Institute of Technology (KTH) in Stockholm.

Techniques:

Journal: Aging Cell

Article Title: Stem cell secretome treatment improves whole‐body metabolism, reduces adiposity, and promotes skeletal muscle function in aged mice

doi: 10.1111/acel.14144

Figure Lengend Snippet: Whole‐Body Metabolic Profile. Oxygen consumption (VO 2 – ml/kg/hr) and carbon dioxide production (VCO 2 – ml/kg/hr) across 24 h in comprehensive lab animal monitoring system (CLAMS) for control and secretome‐treated mice (a, b). 24‐h average VO 2 (c) and VCO 2 (d), 12‐h average dark cycle respiratory exchange ratio (RER – VCO 2 /VO 2 ; e), 24‐h average energy expenditure (f; kcal/kg/hr), activity (g; movement – X + Y + Z), and food intake (g) (h). All data presented as mean ± SD, white bars represent controls while blue squares represent secretome‐treated mice. n = 6 for both groups. * indicates significant difference between conditions for the indicated timepoints with * = p < 0.05, ** = p < 0.01, and *** = p < 0.001.

Article Snippet: Cultured media collected from these cells was pooled, sterile filtered, concentrated, and prepared as a USP‐grade cell‐free stem cell‐based secretome product (IMMUNA; Immunis, Inc., Irvine, CA).

Techniques: Control, Activity Assay

Journal: Aging Cell

Article Title: Stem cell secretome treatment improves whole‐body metabolism, reduces adiposity, and promotes skeletal muscle function in aged mice

doi: 10.1111/acel.14144

Figure Lengend Snippet: Whole body Tissue and Physical Function Changes. Weekly changes lean mass (a), fat mass (b), body fat % (c), and body mass (d) for control and secretome‐treated mice. Weekly whole‐body grip strength (e) and change (Δ) in rotarod performance time from baseline (f). Quadriceps mass (g) and fat mass (h) following 4‐weeks. Control mice are represented by black circles and bars while secretome‐treated mice are noted by blue squares and bars. All data presented as mean ± SEM. (a–h) control mice ( n = 15), secretome‐treated mice ( n = 16). Weekly changes analyzed via mixed‐effects model with Holm‐Bonferroni multiple comparisons plus planned comparison t ‐tests at the 4‐week timepoint. # indicates significant difference ( p < 0.05) from baseline for respective group. * indicates significant difference ( p < 0.05) between groups at the indicated time point.

Article Snippet: Cultured media collected from these cells was pooled, sterile filtered, concentrated, and prepared as a USP‐grade cell‐free stem cell‐based secretome product (IMMUNA; Immunis, Inc., Irvine, CA).

Techniques: Control, Comparison

Journal: Aging Cell

Article Title: Stem cell secretome treatment improves whole‐body metabolism, reduces adiposity, and promotes skeletal muscle function in aged mice

doi: 10.1111/acel.14144

Figure Lengend Snippet: Skeletal Muscle Morphology. Average quadriceps fiber cross sectional area μm 2 (a), minimum feret diameter μm 2 (b), and fiber type proportion (c; MyHC – IIa/IIb %) for control ( n = 8) and secretome treated ( n = 8) mice. Size distribution (%) for total (e), IIa (f) and IIb (g) fiber types across 500 μm 2 increments. Representative histochemical image of fiber type including cell border with laminin in blue, MyHC IIa in green, MyHC IIb in red, and scale bar of 50 μm (d). All data presented as mean ± SD, white circles and bars represent controls while blue squares and bars represent secretome‐treated mice. n = 8 for each group. Analyzed via t ‐tests and mixed effects models with Holm‐Bonferroni comparisons. * indicates significant difference between groups at indicated category with * = p < 0.05, ** = p < 0.01, *** = p < 0.001.

Article Snippet: Cultured media collected from these cells was pooled, sterile filtered, concentrated, and prepared as a USP‐grade cell‐free stem cell‐based secretome product (IMMUNA; Immunis, Inc., Irvine, CA).

Techniques: Control

Journal: Aging Cell

Article Title: Stem cell secretome treatment improves whole‐body metabolism, reduces adiposity, and promotes skeletal muscle function in aged mice

doi: 10.1111/acel.14144

Figure Lengend Snippet: Skeletal Muscle Remodeling. Muscle satellite cell content (Pax7 + /DAPI + − co‐localization) corrected to number of fibers (a). Representative image of satellite cell localization with PAX7 + in off‐red/pink, laminin fiber borders in green, DAPI in blue, satellite cells indicate by white arrows, and scale bar of 50 μm 2 (b). Fiber capillarization (CD31 + ) corrected to number of muscle fibers (c). Representative image of capillarization with CD31 + in red, laminin in green, and DAPI in blue (d). Ratio of B‐CHP to COL‐IV (e) and representative image with B‐CHP in purple and COL‐IV in yellow (f). All data presented as mean ± SD, white circles and bars represent controls while blue squares and bars represent secretome‐treated mice. Control mice ( n = 8), secretome‐treated mice ( n = 7–8), right (injected) quadriceps assessed. Analyzed via t ‐tests. * indicates significant difference between conditions for the indicated timepoints with * = p < 0.05, ** = p < 0.01.

Article Snippet: Cultured media collected from these cells was pooled, sterile filtered, concentrated, and prepared as a USP‐grade cell‐free stem cell‐based secretome product (IMMUNA; Immunis, Inc., Irvine, CA).

Techniques: Control, Injection

Journal: Aging Cell

Article Title: Stem cell secretome treatment improves whole‐body metabolism, reduces adiposity, and promotes skeletal muscle function in aged mice

doi: 10.1111/acel.14144

Figure Lengend Snippet: Adipose Morphology and Muscle Lipid Content. Average cellular diameter μm of I‐WAT (a) and E‐WAT (b) depots. Size distribution (%) of I‐WAT (c) and E‐WAT (d) cells across 5 μm increments. Average liver lipid droplet (e) and fibrosis (f; trichrome staining) area (%) as assessed with H&E. Representative image of I‐WAT and E‐WAT depots as well as liver H&E and trichrome staining with scale bar 50 μm (g). Protein phosphorylation status for protein kinase B (Akt) and hormone sensitive lipase (HSL) for I‐WAT and E‐WAT depots and representative western blot image (h). Muscle lipid content including total triglycerides (TAGs) diglycerides (DAGs), ceramides (Cer), and C18:0 ceramide (C18:0 Cer). All data presented as mean ± SD, white circles and bars represent controls while blue squares and bars represent secretome treated groups. (a–g) n = 8 for each group, (h–i) n = 7 for control, n = 6 for secretome, (i) n = 6 for control, n = 8 for secretome. Analyzed via t ‐tests (a, b, e, f, h, i) or two‐way ANOVA with Holm‐Bonferroni comparison (c, d). * indicates significant difference between groups at indicated category with * = p < 0.05, ** = p < 0.01.

Article Snippet: Cultured media collected from these cells was pooled, sterile filtered, concentrated, and prepared as a USP‐grade cell‐free stem cell‐based secretome product (IMMUNA; Immunis, Inc., Irvine, CA).

Techniques: Staining, Phospho-proteomics, Western Blot, Control, Comparison

Journal: Aging Cell

Article Title: Stem cell secretome treatment improves whole‐body metabolism, reduces adiposity, and promotes skeletal muscle function in aged mice

doi: 10.1111/acel.14144

Figure Lengend Snippet: Direct and Indirect Cellular Experiments. Cell culture design for media replacement and cultured media (CM) experiments (a). Average myotube area (%) (b) and myonuclear fusion index ( au ) (c) for control, secretome treated, control CM, and secretome CM conditions in differentiated C2C12 myotubes. Interleukin 6 (IL‐6) content in the culture media collected from secretome treated (4%) and control C2C12 myotubes (Fold change) (d). Average lipid droplet area corrected to DAPI area (Fold Change) in 3T3‐L1 adipocytes for control, 5 and 20% secretome product media replacement (e). Phosphorylated corrected to total Akt protein (fold change) for 20% secretome treated and control 3T3‐L1 adipocytes following overnight fast and insulin (100 nM) stimulation (f). Average lipid droplet area corrected to DAPI area (Fold Change) in 3T3‐L1 adipocytes for control and 20% media replacement with culture media from control and secretome treated C2C12 cells (g). Representative images of myotubes (h) and adipocytes treated with secretome (i) and culture media (j). (b–g) n = 4–7 per group or replicate. Analyzed via one‐way ANOVA with Holm‐Bonferroni comparison (b–c, e, g) or t ‐tests (d, f). * indicates significant difference between groups as indicated with * = p < 0.05, ** = p < 0.01, *** = p < 0.001.

Article Snippet: Cultured media collected from these cells was pooled, sterile filtered, concentrated, and prepared as a USP‐grade cell‐free stem cell‐based secretome product (IMMUNA; Immunis, Inc., Irvine, CA).

Techniques: Cell Culture, Control, Comparison